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Abstract:

There are provided a bio-signal analyzer using a sensor capable of
detecting, even though it is non-invasive, a more prominent bio-signal,
and a seat using the bio-signal analyzer. Air cushions (10), which are
sensors detecting a bio-signal in a non-invasive manner, are disposed at
the positions corresponding respectively to left and right iliocostalis
lumborum muscles of a person, in a substantially vertically long state
along the iliocostalis lumborum muscles, with upper ends thereof being
set at least at the height corresponding to a lower face of a human
diaphragm. In the diaphragm, bio-signals such as heartbeats, breaths, or
pulsations of aorta passing through the vicinity of the diaphragm are
resonated and amplified. Further, the iliocostalis lumborum muscles are
at positions where they are easily vibrated by pulsations of aorta
passing through the vicinity of the lumbar region. Therefore, by
disposing the air cushions (10) as described above, bio-signals amplified
by the diaphragm and the iliocostalis lumborum muscles can be detected.

Claims:

1. A bio-signal analyzer, comprising:an air cushion having an air bag
formed by sealing except an air inlet/outlet port and a resilience
applying member, which applies resilience in an expansion direction to
the air bag when air is exhausted from the inlet/outlet port by pressing
with a load, and allows air to enter the air bag through the inlet/outlet
port accompanying decrease of the load, the air cushion being
incorporated in a portion supporting a vicinity of the lumbar region of a
person in a human body support means; andan analyzing means analyzing a
human condition from an air pressure variation in the air cushion
generated by a human bio-signal,wherein the air cushion is disposed at
least at one of positions corresponding respectively to left and right
iliocostalis lumborum muscles of a person, in a substantially vertically
long state along the iliocostalis lumborum muscles, and has a length
allowing to set an upper end thereof at least at a height corresponding
to a lower face of a human diaphragm.

2. The bio-signal analyzer according to claim 1, whereinthe length of the
air cushion is in a range of 150 mm to 300 mm.

3. The bio-signal analyzer according to claim 1, whereinthe resilience
applying member is made of a resilient member which is accommodated in
the air bag and applies resilience to the air bag from inside.

4. The bio-signal analyzer according to claim 3, whereinthe resilient
member is formed of a three-dimensional solid knitted fabric.

5. The bio-signal analyzer according to claim 1, whereinthe air cushion
comprises two air bags, and has a structure using the two air bags
overlapping each other.

6. The bio-signal analyzer according to claim 5, whereinthe analyzing
means is configured to perform analysis using a sum of values of
respective air pressure variations of the two air bags of the air
cushion.

7. A seat comprising air cushions incorporated in a portion supporting a
vicinity of a lumbar region in a seat back, wherein:the air cushions each
comprise an air bag formed by sealing except an air inlet/outlet port and
a resilience applying member, which applies resilience in an expansion
direction to the air bag when air is exhausted from the inlet/outlet port
by pressing with a load, and allows air to enter the air bag through the
inlet/outlet port accompanying decrease of the load;the air cushions are
disposed at least at one of positions corresponding respectively to left
and right iliocostalis lumborum muscles of a person, in a substantially
vertically long state along the iliocostalis lumborum muscles, with upper
ends thereof being set at least at a height corresponding to a lower face
of a human diaphragm; andthe air cushions allow to detect an air pressure
variation in the air cushions generated by a human bio-signal so as to
analyze a human condition.

8. The seat according to claim 7, whereinthe length of the air cushions is
in a range of 150 mm to 300 mm.

9. The seat according to claim 8, whereinthe air cushions are disposed so
that respective inside lower ends of the air cushions are located in
ranges of 20 mm to 80 mm leftward and rightward respectively from a
center of the seat back forming the seat and in a range of 10 mm to 80 mm
upward along the seat back from a boundary between a seat cushion and the
seat back.

10. The seat according to claim 9, whereinthe air cushions are disposed so
that respective inside upper ends of the air cushions are located in
ranges of 40 mm to 100 mm leftward and rightward respectively from the
center of the seat back and separated from the center of the seat back
farther than the inside lower ends.

11. The seat according to claim 7, whereinthe resilience applying member
is made of a resilient member which is accommodated in the air bag and
applies resilience to the air bag from inside.

12. The seat according to claim 11, whereinthe resilient member is formed
of a three-dimensional solid knitted fabric.

13. The seat according to claim 7, whereinthe air cushions each comprise
two air bags, and have a structure using the two air bags overlapping
each other.

14. The seat according to claim 13, whereinthe analyzing means is
configured to perform analysis using a sum of values of respective air
pressure variations of the two air bags of the air cushions.

15. The seat according to claim 7, further comprisingan analyzing means
analyzing a human condition from an air pressure variation in the air
cushions generated by a human bio-signal, the analyzing means attached to
a portion of one of the seat cushion and the seat back.

16. A bio-signal analyzing method using an air cushion incorporated in a
portion supporting a vicinity of a lumbar region in a seat back, the
method comprising:using as the air cushion an air cushion having an air
bag formed by sealing except an air inlet/outlet port and a resilience
applying member, which applies resilience in an expansion direction to
the air bag when air is exhausted from the inlet/outlet port by pressing
with a load, and allows air to enter the air bag through the inlet/outlet
port accompanying decrease of the load;setting the air cushion at least
at one of positions corresponding respectively to left and right
iliocostalis lumborum muscles of a person, in a substantially vertically
long state along the iliocostalis lumborum muscles, with upper ends
thereof being at least at a height corresponding to a lower face of a
human diaphragm; anddetecting an air pressure variation in the air
cushion generated by a breath, a heartbeat or a voice.

17. The bio-signal analyzing method according to claim 16, further
comprisingdetecting an air pressure variation in the air cushion
generated by a voice, so as to determine a human condition.

18. The bio-signal analyzing method according to claim 16, further
comprisingdetecting an air pressure variation in the air cushion
generated by a is breath, so as to determine a state of a heartbeat.

Description:

TECHNICAL FIELD

[0001]The present invention relates to a technique for detecting a
bio-signal to analyze the condition of a human body, and particularly
relates to a bio-signal analyzer using air cushions capable of detecting
a bio-signal non-invasively, a seat using the bio-signal analyzer, and a
bio-signal analyzing method.

BACKGROUND ART

[0002]In late years, monitoring the human condition of a driver while
driving has been drawing attention as a measure for preventing a traffic
accident. For example, Patent Documents 1 to 3 disclose a technique to
detect vibration on a body surface accompanying beating of the heart with
a piezoelectric element (piezoelectric film sensor) in a thin film form
attached to a cushion material forming a seat cushion. This technique is
to monitor the human condition by chaos analysis of output of the
piezoelectric element and does not require attaching of a large
monitoring device to the head, allowing easy evaluation of the human
condition of a driver.

[0003]The technique disclosed in Patent Documents 1 to 3 is to detect very
small, minute vibration on the skin surface of buttocks transmitted
accompanying heartbeats and breaths, and requires highly sensitive
sensors. Particularly while idling or traveling, there is large influence
of vibration (noise signal) due to external factors inputted via the
vehicle body. For clear distinction from noise signals, for example in
WO2005/092193, the applicants have proposed to obtain time-series data of
a gradient of an amplitude change ratio (gradient of a power value),
which is obtained by obtaining the rate of change of displacement
(amplitude) of a bio-signal and further performing slide calculation of
the rate of change a predetermined number of times at a predetermined
slide overlap rate, or obtain time-series data of a maximum Lyapunov
index gradient, which is obtained by similarly performing slide
calculation of the maximum Lyapunov index of a chaos indicator. The
respective time-series data of gradients obtained as above allow
actualization of fluctuating waveform data (data of biological
fluctuation) peculiar to bio-signals, and thereby many noise signals can
be cut off. Such an approach by the applicants has an advantage that
minute non-invasively measured bio-signals can be extracted, but the
bio-signals detected with sensors are desired to be more prominent
signals than minute signals.

[0004]The present invention is made in consideration of the foregoing
situation, and an object thereof is to provide a bio-signal analyzer
using a sensor capable of detecting a prominent bio-signal in a
non-invasive manner just by seating, a seat using the bio-signal
analyzer, and a bio-signal analyzing method. Further, another object of
the invention is to provide a bio-signal analyzer which allows to
increase body supportability by disposing this sensor and thereby
increase body pressure dispersibility, and a seat using this bio-signal
analyzer.

Means for Solving the Problems

[0005]To solve the above-described problems, a bio-signal analyzer of the
present invention includes an air cushion having an air bag formed by
sealing except an air inlet/outlet port and a resilience applying member,
which applies resilience in an expansion direction to the air bag when
air is exhausted from the inlet/outlet port by pressing with a load, and
allows air to enter the air bag through the inlet/outlet port
accompanying decrease of the load, the air cushion being incorporated in
a portion supporting a vicinity of the lumbar region of a person in a
human body support means, and an analyzing means analyzing a human
condition from an air pressure variation in the air cushion generated by
a human bio-signal. The air cushion is disposed at least at one of
positions corresponding respectively to left and right iliocostalis
lumborum muscles of a person, in a substantially vertically long state
along the iliocostalis lumborum muscles, and has a length allowing to set
an upper end thereof at least at a height corresponding to a lower face
of a human diaphragm.

[0006]Preferably, the length of the air cushion is in a range of 150 mm to
300 mm.

[0007]Preferably, the resilience applying member is made of a resilient
member which is accommodated in the air bag and applies resilience to the
air bag from inside, and the resilient member is formed of a
three-dimensional solid knitted fabric.

[0008]Further, preferably, the air cushion includes two air bags, and has
a structure using the two air bags overlapping each other. In this case,
preferably, the analyzing means is configured to perform analysis using a
sum of values of respective air pressure variations of the two air bags
of the air cushion.

[0009]Furthermore, a seat of the present invention includes air cushions
incorporated in a portion supporting a vicinity of a lumbar region in a
seat back. The air cushions each include an air bag formed by sealing
except an air inlet/outlet port and a resilience applying member, which
applies resilience in an expansion direction to the air bag when air is
exhausted from the inlet/outlet port by pressing with a load, and allows
air to enter the air bag through the inlet/outlet port accompanying
decrease of the load. The air cushions are disposed at least at one of
positions corresponding respectively to left and right iliocostalis
lumborum muscles of a person, in a substantially vertically long state
along the iliocostalis lumborum muscles, with upper ends thereof being
set at least at a height corresponding to a lower face of a human
diaphragm. The air cushions allow to detect an air pressure variation in
the air cushions generated by a human bio-signal so as to analyze a human
condition.

[0010]Preferably, the length of the air cushions used in the seat is in a
range of 150 mm to 300 mm.

[0011]Further, preferably, the air cushions are disposed so that
respective inside lower ends of the air cushions are located in ranges of
20 mm to 80 mm leftward and rightward respectively from a center of the
seat back forming the seat and in a range of 10 mm to 80 mm upward along
the seat back from a boundary between a seat cushion and the seat back.

[0012]Further, preferably, the air cushions are disposed so that
respective inside upper ends of the air cushions are located in ranges of
40 mm to 100 mm leftward and rightward respectively from the center of
the seat back and separated from the center of the seat back farther than
the inside lower ends.

[0013]Further, preferably, the resilience applying member used in the seat
is made of a resilient member which is accommodated in the air bag and
applies resilience to the air bag from inside, and the resilient member
is formed of a three-dimensional solid knitted fabric. Further,
preferably, the air cushions each include two air bags, and have a
structure using the two air bags overlapping each other. In this case,
preferably, the analyzing means is configured to perform analysis using a
sum of values of respective air pressure variations of the two air bags
of the air cushions.

[0014]Further, preferably, the seat further includes an analyzing means
analyzing a human condition from air pressure variation data in the air
cushions generated by a human bio-signal, the analyzing means attached to
a portion of one of the seat cushion and the seat back.

[0015]Furthermore, the present invention provides a bio-signal analyzing
method using an air cushion incorporated in a portion supporting a
vicinity of a lumbar region in a seat back, the method including:

[0016]using as the air cushion an air cushion having an air bag formed by
sealing except an air inlet/outlet port and a resilience applying member,
which applies resilience in an expansion direction to the air bag when
air is exhausted from the inlet/outlet port by pressing with a load, and
allows air to enter the air bag through the inlet/outlet port
accompanying decrease of the load;

[0017]setting the air cushion at least at one of positions corresponding
respectively to left and right iliocostalis lumborum muscles of a person,
in a substantially vertically long state along the iliocostalis lumborum
muscles, with upper ends thereof being at least at a height corresponding
to a lower face of a human diaphragm; and

[0018]detecting an air pressure variation in the air cushion generated by
a breath, a heartbeat or a voice.

[0019]Preferably, the above method of the present invention further
includes detecting an air pressure variation in the air cushion generated
by a voice, so as to determine a human condition.

[0020]Preferably, the above method of the present invention further
includes detecting an air pressure variation in the air cushion generated
by a breath, so as to determine a state of a heartbeat.

Effect of the Invention

[0021]In the present invention, air cushions, which are sensors detecting
a bio-signal in a non-invasive manner, are disposed at least at one of
the positions corresponding respectively to left and right iliocostalis
lumborum muscles of a person, in a substantially vertically long state
along the iliocostalis lumborum muscles, with upper ends thereof being
set at least at the height corresponding to a lower face of a human
diaphragm. In the diaphragm, bio-signals such as heartbeats, breaths, or
pulsations of aorta passing through the vicinity of the diaphragm are
resonated and amplified. Further, the iliocostalis lumborum muscles are
at positions where they are easily vibrated by pulsations of aorta
passing through the vicinity of the lumbar region. Therefore, with the
air cushions being disposed as described above, by just sitting on the
seat, it becomes possible to use the diaphragm and the iliocostalis
lumborum muscles to detect bio-signals amplified by them, without putting
on any kind of measuring device on the body.

[0022]Of course, for example, when it is arranged to set a piezoelectric
element or the like to a position close to the heart of the person, the
detection sensitivity to heartbeats or the like increases. But in this
case, a dedicated sensor for detecting a bio-signal must be arranged. For
example, when such a sensor is arranged at a position corresponding to
the heart in the case of a vehicle seat, it is necessary to separately
provide a member needed in terms of functions of the seat, such as a
lumbar support. In contrast, in the present invention, by disposing the
air cushions in a substantially vertically long state along the
iliocostalis lumborum muscles, the air cushions are able to function as a
bio-signal detection sensor while having the function as a lumbar support
to support the lumbar region. Moreover, using the resonating function of
the diaphragm and the vibrating function of the iliocostalis lumborum
muscles, a bio-signal can be detected with high sensitivity. That is, a
breath, a heartbeat, a voice, or the like is transmitted to the air
cushions as solid propagation is sound via the diaphragm and other
muscles. The solid propagation sound at this time resonates, with its
pressure value and frequency, the air bags of the air cushions having
predetermined surface rigidity, and further vibrates connecting fibers of
three-dimensional solid knitted fabrics which are resilient members
arranged therein, thereby vibrating air in the air bags to generate an
air pressure variation, or pressing the air cushions to generate an air
pressure variation. Thus, a bio-signal can be detected by measuring the
air pressure variation generated in this manner. In particular, in the
case of a voice signal, when a human voice propagates through the air, it
is at a high frequency of several hundred Hz to several kHz and a
dedicated device is needed to sample the voice signal. With the present
invention, since the air cushions are provided along the iliocostalis
lumborum muscles as described above, the voice signal can be sampled as
vibration at lower frequency as solid propagation sound via the diaphragm
and other muscles than the air propagation sound. The degree of tension
of muscles changes between a tense mental and physical state and a
relaxed mental and physical state. Accordingly, also with a voice
propagating the diaphragm and other muscles, the vibration of these
muscles changes depending on whether in a tense state or not. Therefore,
it is possible to presume the state of the nervous system of a sitter
(driver) by detecting a voice. Further, with the present invention, the
heartbeat can be measured directly, but when it is hindered by vibration
inputted from the outside when the automobile is traveling, the state of
heartbeat variation can be estimated from the air pressure variation by
breathing.

[0023]Further, since the air cushions are arranged respectively to the
positions corresponding to the iliocostalis lumborum muscles of a human
body, the vicinity of a body side of the lumbar region is supported, and
the posture thereof becomes stable. Moreover, since the air cushions fit
the shape of the lumbar region, the body pressure dispersibility
increases, and the vibration absorbing characteristic and the seating
comfort improve.

BRIEF DESCRIPTION OF DRAWINGS

[0024]FIG. 1 is a view showing the structure of a bio-signal analyzer
according to an embodiment of the present invention;

[0025]FIG. 2 is a view showing a state that the bio-signal analyzer
according to the embodiment is incorporated in a seat;

[0026]FIG. 3 is a cross-sectional view of one air bag forming an air
cushion, and a resilience applying member accommodated in the air bag;

[0027]FIG. 4 is a graph showing a load-displacement characteristic of the
air cushion shown in FIG. 3;

[0028]FIG. 5 is a view showing an example of a specific structure of a
seat according to the embodiment;

[0029]FIG. 6 is a view showing another example of a specific structure of
a seat according to the embodiment;

[0030]FIG. 7 is a view showing a main part of a more preferable structure
of the seat used in FIG. 6;

[0031]FIG. 8 is a graph showing acceleration transmissibilities when
vibration is applied with random waves to the seat in FIG. 6 and a seat
having a conventional structure;

[0032]FIGS. 9A to 9H are graphs showing body pressure distributions in a
seat back part of the seat in FIG. 6 with respect to frequencies from 3
Hz to 10 Hz;

[0033]FIGS. 10A to 10H are graphs showing body pressure distributions in a
seat back part of a seat having a conventional structure with respect to
frequencies from 3 Hz to 10 Hz;

[0035]FIGS. 12 are graphs showing results of test example 1, where FIG.
12A shows a spectral waveform of breath components obtained from a
distortion type respirometer and a spectral waveform of breath components
obtained from the air cushions, and FIG. 12B shows a correlation function
of them;

[0037]FIGS. 14 are graphs showing results of test example 2, where FIG.
14A shows a spectral waveform of breath components obtained from a
distortion type respirometer and a spectral waveform of breath components
obtained from the air cushions 10, and FIG. 14B shows a correlation
function of them;

[0038]FIGS. 15 are graphs showing results of test example 3, where FIG.
15A shows time-series waveforms of respective gradients of power values
and maximum Lyapunov indexes related to the breath components obtained
from the air cushions, and FIG. 15B shows time-series waveforms of
respective gradients of power values and maximum Lyapunov indexes related
to the heartbeat components obtained from the air cushions, and FIG. 15C
shows time-series waveforms of frequencies of the heartbeat components
and the breath components obtained from the air cushions;

[0039]FIG. 16A is a graph showing time-series waveforms of respective
gradients of power values and maximum Lyapunov indexes of the finger tip
volume pulse waves, and FIG. 16B is a graph showing time-series changes
of distribution ratios of θ wave, α wave, and β wave of
brain waves;

[0040]FIG. 17A is a graph showing comparison of the degree of fatigue
obtained from time-series waveforms of gradients of breath components
obtained from the air cushions with the degree of fatigue obtained from
gradient time-series waveforms of finger tip volume pulse waves, and FIG.
17A is a graph showing comparison of the degree of fatigue obtained from
time-series waveforms of gradients of heartbeat components obtained from
the air cushions with the degree of fatigue obtained from gradient
time-series waveforms of finger tip volume pulse waves;

[0041]FIGS. 18 are graphs showing results of verification of effectiveness
of bio-signal sampling when values of air pressure variations of air bags
of the air cushions are addition processed and when they are subtraction
processed, where FIG. 18A shows original waveforms in time series of the
air bags, original waveforms in time series when values of air pressure
variations obtained from the air bags are added (addition waveform), and
original waveforms in time series when the values are subtracted
(subtraction waveform), FIG. 18B shows time-series waveforms of the air
bags with respect to heartbeat components separated by filtering
processing, FIG. 18C is shows time-series waveforms when the time-series
waveforms of heartbeat components of a detection sensor and a dummy
sensor in FIG. 18B are addition processed and when they are subtraction
processed, FIG. 18D shows time-series waveforms of the air bags with
respect to breath components separated by filtering processing, FIG. 18E
shows time-series waveforms when the time-series waveforms of breath
components of the detection sensor and the dummy sensor in FIG. 18D are
addition processed and when they are subtraction processed;

[0042]FIG. 19A shows a time-series original waveform of a voice signal
obtained from the air cushions, and FIG. 19B is a graph showing frequency
analysis results thereof;

[0043]FIGS. 20 shows time-series waveforms of voice signals of three
subjects, where FIG. 20A shows a time-series waveform indicating a voice
signal of a male in his thirties (middle to high voice), FIG. 20B shows a
time-series waveform indicating a voice signal of a male in his twenties
(low voice), FIG. 20C shows a time-series waveform indicating a voice
signal of a female in her twenties (thin and high voice);

[0049]FIG. 26 shows graphs showing time-series waveforms of heartbeat
components and breath components of one subject of test example 7 in the
morning, at noon, and at night;

[0050]FIG. 27 shows graphs showing time-series waveforms of heartbeat
components and breath components of another subject of test example 7 in
the morning, at noon, and at night;

[0051]FIG. 28 shows graphs showing time-series waveforms of heartbeat
components and breath components of still another subject of test example
7 in the morning, at noon, and at night;

[0052]FIG. 29 is a view for describing the structure of an air cushion in
which a buffer material (three-dimensional solid knitted fabric and
viscoelastic urethane) for damping vibration is sandwiched between the
two air bags; and

[0053]FIG. 30A is a view showing an embodiment in which air cushions are
incorporated in an auxiliary cushion (cushion for seat), and FIG. 30B is
a partial cross-sectional view of FIG. 30A.

[0067]Hereinafter, the present invention will be described in more detail
based on embodiments of the invention shown in the drawings. FIG. 1 is a
view showing a bio-signal analyzer 1 according to this embodiment. FIG. 2
is a view showing a state that this bio-signal analyzer 1 is applied to a
seat 100. The bio-signal analyzer 1 has air cushions 10, an air pressure
measuring instrument 20, and an analyzing means 30.

[0068]The air cushions 10 each have air bags 11 and a resilience applying
member 12. The air bags 11 need to have rigidity required for solid
propagation of a bio-signal and a human voice. This is because solid
propagation sound attenuates when the rigidity is insufficient. Further,
the air cushions 10 of this embodiment each include two air bags 11, 11
sandwiching a boundary portion 13, and as shown in FIG. 2, the two air
bags 11, 11 in use are folded in two to overlap each other. The air bags
11, 11 are, as shown in FIG. 1, each formed in an arbitrary shape with a
predetermined size, but preferably have a width of 40 mm to 100 mm and a
length of 150 mm to 300 mm. Each air bag 11 is provided with an air
inlet/outlet port 11 a in an arbitrary portion, which is one end in a
length direction in FIG. 1, and the other portion on the periphery is
sealed entirely. The air pressure measuring instrument 20 is connected to
the inlet/outlet port 11 a. Thus, an air pressure variation is detected
by the air pressure measuring instrument 20 when a load is applied to the
air cushions 10 or when a load applied thereto decreases.

[0069]The air cushions 10 are incorporated in the vicinity of the lumbar
region in a seat back 110. Specifically, in this embodiment, at the
position corresponding to the left and right iliocostalis lumborum
muscles of a person seated on the seat 100, the air cushions folded in
two are disposed as shown in FIG. 2 in a substantially vertically long
state along the iliocostalis lumborum muscles as described above. The
iliocostalis lumborum muscles are located such that the distance between
the iliocostalis lumborum muscles (that is, respective distances from the
spine to the iliocostalis lumborum muscles) is shorter in a region closer
to the buttocks than in a region closer to the diaphragm. Therefore, the
substantially vertically long state means that the two air cushions 10,
10 are disposed slightly obliquely so that the gap therebetween becomes
smaller downward with distance. Further, the air cushions 10, 10 have
upper ends respectively set at least at the height corresponding to a
lower face of the human diaphragm. To set the upper ends at least at the
height corresponding to the lower face of the human diaphragm when
disposed in the substantially vertically long state corresponding to the
iliocostalis lumborum muscles, it is preferable that the air cushions 10,
10 each have a length of 150 mm to 300 mm as mentioned above. In
addition, it is preferable that the upper ends of the air cushions 10,
10', when disposed at a highest position, are set not higher than the
height corresponding to an upper face of the diaphragm.

[0070]To dispose the air cushions 10, 10 having a length in the range of
150 mm to 300 mm along the iliocostalis lumborum muscles with the upper
ends being at least at the height corresponding to the lower face of the
diaphragm, the air cushions 10, 10 just need to be disposed so that
respective inside lower ends 10a, 10a of the air cushions 10, 10 are
located in the ranges of 20 mm to 80 mm leftward and rightward
respectively from the center B of the seat back 110 and in the range of
10 mm to 80 mm upward along the seat back 110 from the boundary between
the seat cushion 120 and the seat back 110. Further, the air cushions 10,
10 are also disposed so that respective inside upper ends 10b, 10b
thereof are located in the ranges of 40 mm to 100 mm leftward and
rightward respectively from the center B of the seat back 110 and
separated farther from the center B of the seat back 110 than the inside
lower ends 10a, 10a.

[0071]The air bags 11 have a characteristic to resonate when solid
propagation sound of a bio-signal of heartbeat, voice, breath, or the
like is transmitted thereto via human muscles such as iliocostalis
lumborum muscles. Accordingly, as described above, the air bags need to
have high rigidity, and preferred to be a material having one or more
gain of amplitude characteristic.

[0072]The resilience applying member 12 is formed to have a size that can
be accommodated in each air bag 11, and applies resilience to each air
bag 11 from the inside. For the resilience applying member 12, it is
preferable to use a three-dimensional solid knitted fabric, by which high
resilience can be obtained, and which exhibits a soft spring
characteristic by a load concentrated at one point but exhibits a linear
and rigid spring characteristic in a surface contact with a predetermined
area, for example, a surface contact in the range of 98 mm diameter or
larger corresponding to the diameter of a human buttock on one side. Due
to having such characteristics, the three-dimensional solid knitted
fabric has spring characteristics approximating to that of human muscles,
which is relatively soft when locally pressed but is relatively rigid
when pressed with a predetermined area. For accommodating in the air bag
11, for example, a strip-shaped three-dimensional solid knitted fabric
having a width of about 10 mm to 90 mm and a length of about 80 mm to 280
mm is used. The resilience applying member 12 may be formed of one such
strip-shaped three-dimensional solid knitted fabric, or as shown in FIG.
3, two such three-dimensional solid knitted fabrics in a layered state
may be accommodated in the air bag 2.

[0073]The three-dimensional solid knitted fabric forming the resilience
applying member 12 is knitted by reciprocating a connecting yarn between
a pair of ground knitted fabrics positioned with a predetermined gap
therebetween, and is formed in a predetermined shape using a double
raschel knitting machine or the like. Here, the present invention
attempts to capture a pulse wave flowing through a blood vessel by
pumping of blood by the heart, a breath, or a voice as a pressure
variation by solid propagation via muscles. In this situation, the
resilience applying members 12 arranged in the air cushions 10, 10'
repeat compression and restoration by this solid propagation. The fact
that the three-dimensional solid knitted fabric has the spring
characteristic approximating to that of human muscles means that the
pressure (internal pressure) caused by vibration of actual human muscles
and the pressure (external pressure) accompanying compression and
restoration of the three-dimensional solid knitted fabric corresponding
thereto are substantially equal, and it can be said that the measurement
of air pressure variation in the air cushion 10 in the present invention
is a technique using the principle of tonometry.

[0074]At this time, due to the pressure value and the frequency of solid
propagation sound of a bio-signal, mainly a heartbeat or a voice for
example, when transmitted as solid propagation sound to the air cushions
10 via muscles, operates to vibrate the air bags 11 since the air bags 11
of the air cushions 10 have predetermined rigidity. Also, due to the
characteristics of the three-dimensional solid knitted fabric
approximating to that of muscles, the vibration of the air bags 11 is
transmitted to the connecting yarn of the three-dimensional solid knitted
fabric, and this vibration operates so as to vibrate the air filled
therein. As a consequence, a variation occurs in the air pressure
measured via the inlet/outlet ports 11a of the air bags 11. On the other
hand, depending on the pressure value and the frequency of solid
propagation sound, for example a breath causes a pressure variation by
compression or restoration of the air cushions 10 corresponding to
movement of muscles accompanying the breath. Therefore, it is preferable
that an overall load-displacement characteristic of the air cushions 10,
including rigidity of the air bags 11 of the air cushions 10,
approximates to a load-displacement characteristic of human muscles. This
makes that human muscles and the air cushions 10 to be in an equilibrium
state as described above, and tension that is about the same as that of
human muscles works on the air cushions 10. Thus, the air cushions 10
respond sensitively to vibration of air due to the aforementioned solid
propagation sound or movement of muscles, thereby allowing an amplified
pressure variation to occur.

[0075]Incidentally, as the three-dimensional solid knitted fabric having
characteristics approximating to human muscles, for example, the
following ones can be used.

[0089]The air pressure measuring instrument 20 is connected to the
inlet/outlet ports 11a of the air cushions 10 as described above. The air
cushions 10 are disposed along the iliocostalis lumborum muscles from the
positions corresponding to the diaphragm as described above. Thus,
heartbeats, breaths, and pulsations are amplified by the diaphragm and
the iliocostalis lumborum muscles and cause an air pressure variation in
the air cushions 10 as described above. Incidentally, to detect the air
pressure variation in the air cushions 10 more prominently, it is
preferable that the air pressure measuring instrument 20 includes a
differential transformer for amplifying the air pressure variation.

[0090]The electrical signal of the detected air pressure variation is sent
to the analyzing means 30. The analyzing means 30 is made up of a
computer in which a computer program analyzing output values of an air
pressure variation so as to analyze the human condition is incorporated.
Further, in this embodiment, as each air cushion 10, one having the two
air bags 11, 11 bounded on the boundary portion 13 is used, and this air
cushion is folded in two and incorporated in the seat 100. The air
pressure variation is sampled from the two air bags 11, 11. The air
pressure variation can be sampled with one air bag, but it is preferable
to use, as in this embodiment, two overlapped air bags 11, 11 and use the
sum obtained by adding the values of air pressure variations obtained
from them. This addition provides a characteristic that, in the
time-series waveforms of air pressure variations detected with the air
bags 11, 11, the waveform of a bio-signal is emphasized in the region
where the bio-signal is sampled, and vibration from the human body
accompanying heartbeats, breaths, voices or the like can be sampled more
precisely. Further, in this embodiment, air pressure variations are
detected from the air cushions 10, 10 disposed on the left and right
sides respectively. This is for responding to a situation that the
seating position is deviated either leftward or rightward, where data
with more excellent detecting sensitivity may be used out of data from
the two air cushions 10, 10. Further, the average of the both can be
adopted. The analyzing means 30 can be disposed by fixing at a position
in the seat 100 where it does not hinder the function of the seat 100.
Particularly, when the seat 100 is one for a vehicle, it becomes possible
to know the human condition of the driver or the like while driving in
real time, by fixing the analyzing means in the seat 100 or incorporating
the analyzing means in an arbitrary portion of the vehicle body. When the
bio-signal analyzer 1 of this embodiment is used for diagnosis purpose or
the like, the air cushions 10 described above can, of course, be disposed
in a chair, a bed or the like for diagnosing, and the analyzing means 30
can be made up of a laptop or desktop computer that is not fixed to the
bed or the like.

[0091]Here, as the computer program set in the analyzing means 30, it is
possible to use, for example, a program determining human conditions such
as hypnagogic symptoms disclosed in WO2005/092193 proposed by the present
applicants, a program quantizing the degree of fatigue disclosed in
WO2005/039415, or the like. By these programs, hypnagogic symptoms or the
degree of fatigue are determined.

TEST EXAMPLE

[0092]A subject was seated on the seat 100 for automobile having the
bio-signal analyzer 1 as shown in FIG. 2, and a test of detecting
bio-signals of the subject by air pressure variation was performed. The
air cushion material 10 used in the test is one, as shown in FIG. 3, in
which the resilience applying member 12 is fitted in the air bag 11. As
the resilience applying member 12, there was used one in which two pieces
of the three-dimensional solid knitted fabric with product number:
T24053AY5-1S made by Asahi Kasei Fibers Corporation, with a thickness of
10 mm, a width of 40 mm, and a length of 220 mm, are overlapped and the
peripheral portions thereof are vibration welded. The air bag 11 in which
the resilience applying member 12 is fitted has dimensions of width of 50
mm and length of 230 mm.

[0093]Here, the air cushion 10 was placed on a measuring board formed of a
rigid flat plate and was pressed with a pressure board having a diameter
of 98 mm in a thickness direction designated by an arrow in FIG. 3, and
thereby the load-displacement characteristic (spring characteristic)
thereof was measured and compared with the load-displacement
characteristic (spring characteristic) of human muscles. The
load-displacement characteristic of human muscles was obtained by
pressing arm muscles with the pressure board having a diameter of 98 mm.
The pressure occurring in the lumbar region or buttocks of a person
seated in an equilibrium state ranges from 60 N to 80 N. In this pressure
range, it can be seen from FIG. 4 that the load-displacement
characteristic of the air cushion 10 approximates to the
load-displacement characteristic of human muscles. Therefore, the air
cushion 10 has the same characteristic as human muscles in terms of
load-displacement characteristic (spring characteristic) when a pressure
ranging from 60 N to 80 N is applied, and is appropriate for capturing
bio-signals occurring through muscles.

[0094]The air cushions 10, 10 are disposed, as described above, in the
portion supporting the lumbar region in the seat 100 for automobile.
Specifically, the respective inside lower ends 10a, 10a of the air
cushions 10, 10 were set to positions at 40 mm leftward and rightward
respectively from the center of the seat back 110, and at 40 mm upward
along the seat back 10 from the boundary between the seat cushion 120 and
the seat back 110. The respective inside upper ends 10b, 10b of the air
cushions 10, 10 were set to positions at 80 mm leftward and rightward
respectively from the center of the seat back 110. When a Japanese male
subject 167 cm tall, weighing 74 kg, and aged 31 sat on the seat 100, the
air cushions 10, 10 were located approximately along the respective left
and right iliocostalis lumborum muscles of the subject, and the
respective upper ends of the air cushions 10, 10 were set at the height
corresponding to the intermediate positions of the lower face and the
upper face of the diaphragm of the subject.

[0095]The seat 100 includes, as shown in FIG. 5 for example, a flat
support member 103 provided on the cushion frame 101 via coil springs 102
and a torsion bar (not shown), and a three-dimensional solid knitted
fabric 104 stretched with a low tension covering the flat support member
103, and so on. By the operations of metal springs such as the coil
springs 102 and the torsion bar, vibration with low frequency and large
amplitude is absorbed, and by the tension of the three-dimensional solid
knitted fabric 104 itself, vibration with high frequency and small
amplitude is absorbed. Particularly, the three-dimensional solid knitted
fabric 104 has a structure suspended by a predetermined tension in any
position of the seat back unit 110 and the seat cushion unit 120, and can
efficiently absorb forward/backward vibration at 5 Hz to 8 Hz inputted to
the seat back unit 110. Therefore, this seat 100 has a quite high ability
to damp external vibration inputted as noise.

[0096]Further, a seat 300 shown in FIG. 6 has a seat cushion unit 310 and
a seat back unit 350, and the seat cushion unit 310 has side frames 317,
317. A torsion bar 311 is provided along a width direction in the
vicinities of front ends of the side frames 317, 317. At end portions of
the torsion bar 311, bent portion of first link plates 312, 312 formed in
a substantially L shape are pivotally supported, and the torsion bar 311
is arranged to be twisted by displacement of the first link plates 112,
312 in a rotational direction. The first link plates 312, 312 in a
substantially L shape each have a tip located more forward than the
disposed position of the torsion bar 311, and a rear end provided in a
direction to be located lower than the disposed position of the torsion
bar 311. Between the tips of the first link plates 312, 312, a front end
support frame 315 is provided transversely.

[0097]Further, in the vicinities of rear ends of the side frames 317, 317,
there are provided second link plates 313, 313 formed in a substantially
L shape with bent portions pivotally supported by the side frames 317,
317 respectively. Further, the second link plates 313, 313 in a
substantially L shape each have a tip located more forward than the
pivotal support positions of the bent portions, and a read end provided
in a direction to be located lower than the pivotal support positions of
the bent portions. Connection link plates 314 are provided respectively
across the rear ends of the second link plates 313, 313 and the rear ends
of the above-described first link plates 312, 312, where the first link
plates 312, 312, the second link plates 313, 313 and the connection link
plates 314 form a parallel link mechanism.

[0098]In this seat 300, since it has the above structure, the operating
directions of the first link plates 312, 312 and the second link plates
313, 313 substantially match in upward and downward directions along the
surface of the seat back 350. Therefore, when the human body vibrates in
an upward direction by input of external vibration, the cushion material
of the seat back 350 moves upward and obliquely rearward together with
the human body. When the human body moves in a downward direction, the
cushion material moves in a direction to push the buttocks forward while
moving downward together with the human body. At the same time, the
cushion material of the seat cushion unit 310 moves in forward and
backward directions along with such input of external vibration.
Consequently, due to the support by the parallel link mechanism pivotally
supported directly by the torsion bar 312, the cushion material of the
seat back unit 350 and the cushion material of the seat cushion unit 310
perform rotation movement following the movement of the human body caused
by the input of external vibration. Thus, there is small relative
movement of the human body and the cushion material, which lowers the
resonance peak, thereby allowing improvement of the vibration absorbing
characteristic. Further, due to the high following ability relative to
movement of the human body, the influence of the input of external
vibration becomes small, and the air pressure variation by a bio-signal
can be detected sensitively when the air cushions 10 are arranged.

[0099]Here, input of upward and downward vibration by which a person feels
unpleasant is roughly divided in two vibration modes. A shaky feeling
that the body is shaken largely and a quivering feeling due to resonance
of internal organs, which occur in the vicinities of 5 Hz and 8 Hz
respectively. Particularly, there is a characteristic in motion of the
lumbar region. The vibration that occurs in the vicinity of 5 Hz causes
bending of the entire spine like rotational movement in forward and
backward directions about and below the chest, while the upper body of
the person barely moves. The vibration in the vicinity of 8 Hz causes the
spine to move upward and downward with the buttocks play a role as a
spring. However, bending of the lumbar vertebral region occurring at the
same time suppresses movement of the upper body. Further, when the masses
of the head and chest are applied to the upper portion of the spine,
movement of the spine upper portion is further restricted. The larger the
balance of head mass of a person, the smaller the influence of the back
of a seat becomes. The smaller the sizes of the body and head of a
person, the more sensitive this person is to back slapping from the back
of a seat. Accordingly, for suppressing vibration transmitted to a human
body, it is preferable that the cushion material of the three-dimensional
solid knitted fabric or the like provided in the seat back part and the
seat cushion part is provided to follow well the motion of a person
corresponding to input of such vibration. Further, with such a structure,
in particular the structure shown in FIG. 6 described above, the air
cushion 10 arranged corresponding to the portion supporting the lumbar
region follows the motion of a person well, together with the cushion
material. Incidentally, it is preferable that the cushion material of the
seat back part is supported to be movable upward and downward by engaging
the cushion material slidably with the frame materials arranged in an
upward and downward direction, and supporting at least one of the upper
portion and the lower portion of the three-dimensional solid knitted
fabric on the back frame via coil springs.

[0100]FIG. 7 shows an example of this, showing a structure in which the
seat back part 350 includes a cushion material 353 on a surface layer, a
base cushion material 351 disposed on a back face side thereof, and a
cushion material 352 for supporting pelvis disposed further on a back
face side thereof. Among them, the base cushion material 351 has a lower
end edge supported by a coil spring 351a coupled to a frame disposed in
the vicinity of a rear portion of the seat cushion part 310, and a resin
member 351b for engagement having a low friction coefficient is attached
to a side edge thereof. This resin member 351b for engagement is engaged
with a frame member disposed along the upward and downward direction in
the vicinity of the side edge of the seat back part 150, and thereby the
base cushion material 351 has a structure capable of vibrating
vertically. The cushion material 352 for supporting pelvis is strained
along the width direction between side frames of the seat back part 350,
and has a structure to support the vicinity of the pelvis while slightly
pressing the pelvis. This facilitates, when external vibration is input,
movement of the cushion material of the seat back part 350, particularly
the base cushion material 351, in upward and downward directions along
the torso line while seated, following the behavior of the human body
when vibrating, thereby reducing relative movement of the human body and
the cushion material.

[0101]Incidentally, the structures shown in FIG. 5 to FIG. 7 are merely
examples. However, such structures are preferable for detecting a
bio-signal because an air pressure variation due to a bio-signal can be
detected sensitively when the air cushions 10 are arranged in the seat
300 shown in FIG. 6 and FIG. 7. To verify this point, a vibration
experiment was conducted such that the seat 300 is attached to a platform
of a vibrator, an acceleration sensor is attached in the vicinity
corresponding to positions below the ischial tuberosities in the seat
cushion, a Japanese male weighing 68 kg is seated on each vehicle seat,
and vibration is applied thereto with random waves. In addition, for
comparison, the same experiment was conducted with a seat having a
conventional structure which does not have the parallel link mechanism
and in which a urethane material is arranged on a cushion pan. FIG. 8
shows acceleration transmissibility (G/G) when vibration is applied with
random waves. FIGS. 9A to 9H are graphs showing body pressure
distributions in the seat back part of the seat 300 having the parallel
link mechanism when random vibration was performed, with respect to
frequencies from 3 Hz to 10 Hz. FIGS. 10A to 10H are graphs showing body
pressure distributions in a seat back part when the same test was
performed while seated on the seat having the conventional structure
formed by supporting a urethane material on a cushion pan, similarly with
respect to frequencies from 3 Hz to 10 Hz.

[0102]As is clear from FIG. 8, the seat 300 has a lower resonance point
than that of the seat having the conventional structure, and it can be
seen that the vibration absorption characteristic in a high frequency
band of 8 Hz and higher is largely improved. Further, normally, when the
spring constant gets softer, the resonance point shifts to a low
frequency but the gain increases. However, the seat 300 has the structure
with a high follow-up ability to motion of a person accompanying input of
vibration, due to an upward and downward movement mechanism of the
parallel link mechanism and the cushion material of the seat back part
350 described above. Accordingly, with respect to motion of a person
along the surface of the seat back part 350 due to the parallel link
mechanism, when the cushion material forming the seat back part 350 is
the three-dimensional solid knitted fabric, relative displacement of the
three-dimensional solid knitted fabric and the person becomes small due
to friction, viscosity, and elasticity, resulting in a skyhook effect
which is felt like parrying. Further, in the vicinity from the pelvis to
the lumbar part of a person, friction force by the pressure bearing
capacity of the cushion material 352 for supporting pelvis shown in FIG.
7 increases. Thus, at the resonance point, a resonance point passing
phenomenon occurs such that an opposite phase occurs relative to input of
vibration in a vertical direction and the gain decreases, and the
vibration absorption characteristic is improved by integral motion of the
human body and the cushion material. Further, when a urethane material or
any other spring structure is adopted, instead of the three-dimensional
solid knitted fabric, for the seat back part 350 of the seat 300 adopting
the parallel link structure, there occurs so to speak a forceful sky-hook
effect by force using collision vibration, resulting in improvement of
vibration characteristic around the resonance point.

[0103]Further, in the seat having the conventional structure, input of
external vibration operates to disturb respiratory movement, but in this
embodiment the support pressure to the lumbar vertebral region is
increased so as to facilitate abdominal breathing. That is, the lumbar
support is not high in a static state, but when vibration is inputted due
to traveling, motion of the parallel link mechanism presses the lumbar
vertebral region against the seat back part 350. Since the cushion
material 352 for supporting pelvis shown in FIG. 7 is disposed for the
lumbar vertebral region, pressing against the seat back part 350 by the
parallel link mechanism causes increase in support pressure to a region
where continuous feeling is missing on the vertical cross section
corresponding to the input vibration, to thereby eliminate a part where a
prominent surface pressure exists. Also, movement of the thoracic
vertebra region is small, and a fluctuation occurs at the lumbar part,
thereby helping respiratory movement. Comparing FIGS. 9 with FIGS. 10 in
this respect, in the seat 300 shown in FIG. 9 the pressure of a pelvis
upper edge increases by any frequency of the external vibration inputted,
and this becomes a support for the pelvis upper edge. It can be seen that
the aforementioned pressure to the region where continuous feeling is
missing on the vertical cross section is increased. Particularly, seeing
data from 7 Hz to 10 Hz, the pressure in the chest region is small,
pressure variation concentrates at the pelvis, and motion of the pelvis
is not hindered, resulting in motion facilitating respiratory movement.
In contrast, in the seat having the conventional structure in FIG. 10,
the pressure in the vicinity of the pelvis upper edge is low, which
provides no support for the pelvis upper edge. The increase of the
support pressure of the lumbar vertebrae corresponding to input vibration
leads to that, when the air cushions 10 are disposed as shown in FIG. 6
disposed at the positions corresponding to the lumbar vertebral region,
the contact between the air cushions 10 and the human body increases, and
the pressure variation in the chest region becomes small. Thus, the
bio-signal detecting sensitivity improves.

[0104]In the following test example, the seat 300 shown in FIG. 6 and FIG.
7 was attached in the driver's seat area of a compact car, and tests were
carried out.

TEST EXAMPLE 1

[0105]Seventeen healthy Japanese males and three healthy Japanese females
aged in their twenties to thirties were selected as subjects. They were
each seated on the seat 300 for five minutes in a resting state with the
vehicle being in a static state, and human conditions in this period were
checked. In test example 1, outputs due to air pressure variations of the
air cushions 10 obtained by the analyzing means 30 from the air pressure
measuring instrument 20 were filtered through an analog signal processing
circuit so as to separate them into breath components and heartbeat
components, and respective spectral waveforms of the heartbeat components
and the breath components were obtained. Incidentally, in the filtering
process, fourth-order filtering is performed in bands of 0.1 Hz to 0.5 Hz
and 0.5 Hz to 2.0 Hz, to thereby separate the breath components and the
heartbeat components. The sampling frequency is 200 Hz and the resolution
is 12 bit.

[0106]Further, to obtain correlativity with bio-signals obtained from the
air cushions 10, an optical finger tip pulse wave meter was attached to
the left index finger of each subject to measure finger tip volume pulse
waves, and a distortion type respirometer was attached to the chest
region of each subject to measure breathing. The measured data were
processed, and spectral waveforms of heartbeats were obtained from the
finger tip volume pulse wave meter and spectral waveforms of breaths were
obtained from the distortion type respirometer.

[0107]FIG. 11A shows the spectral waveform of the heartbeat components
obtained from the finger tip volume pulse waves and the spectral waveform
of the heartbeat components obtained from the air cushions 10. FIG. 11B
is a graph showing the correlation function of them. FIG. 12A shows the
spectral waveform of the breath components obtained from the distortion
type respirometer and the spectral waveform of the breath components
obtained from the air cushions 10. FIG. 12B is a graph showing the
correlation function of them.

[0108]As is clear from these graphs, peaks of the heartbeat components
were obtained at 1.3 Hz from both the finger tip volume pulse waves and
the air cushions 10, and peaks of the breath components were obtained at
0.27 Hz from both the distortion type respirometer and the air cushions
10. In comparison of the 20 subjects, there are differences in
correlativity but the peak frequencies of all the subjects matched. On
the other hand, regarding cross correlation functions, 13 heartbeat
components were obtained in ten seconds, and three breath components were
obtained in ten seconds, which matched the respective spectra. From the
above, in a static seating state, it can be seen that it is possible to
sense heartbeat components and breath components by the bio-signal
analyzer 1 including the air cushions 10 according to the above
embodiment, in both the aspects of frequency axis and time axis.

TEST EXAMPLE 2

[0109]The same test as the test example 1 was carried out on eight
subjects out of the 20 subjects in the test example 1 in an idling state
of an actual vehicle. Results are shown in FIGS. 13 and FIGS. 14. FIG.
13A shows a spectral waveform of heartbeat components obtained from
finger tip volume pulse waves and a spectral waveform of heartbeat
components obtained from the air cushions 10, and FIG. 13B is a graph
showing the correlation function of them. FIG. 14A shows a spectral
waveform of breath components obtained from the distortion type
respirometer and a spectral waveform of breath components obtained from
the air cushions 10, and FIG. 14B is a graph showing the correlation
function of them.

[0110]Peaks of the heartbeat components were obtained at 1.3 Hz from both
the finger tip volume pulse waves and the air cushions 10, and peaks of
the breath components were obtained at 0.25 Hz from both the distortion
type respirometer and the air cushions 10. Regarding cross correlation
functions, 13 heartbeat components were obtained in ten seconds, and
three breath components were obtained in ten seconds, which matched the
respective spectra. In this idling state, heartbeat components were
detected from all the eight subjects, and breath components were detected
from six out of the eight subjects. Therefore, it was made clear that,
also in an idling state, it is possible to sense heartbeat components and
breath components by the bio-signal analyzer 1.

TEST EXAMPLE 3

[0111]Three healthy Japanese male subjects in their twenties to thirties
were seated, each subject was further instructed to close eyes and sleep
after being seated, and a sleep experiment was performed in a resting
posture for 30 minutes. Air pressure variations sampled by the air
cushions 10 of the bio-signal analyzer 1 of the above embodiment were,
similarly to the test example 1 an the test example 2, filtered through
the analog signal processing circuit by the analyzing means 30, and
thereafter separated into breaths components and heartbeat components.
Then time series signals of the heartbeat components and the breath
components were used to create a time-series waveform of a gradient of
power values and a time-series waveform of a gradient of maximum Lyapunov
indexes, respectively, and it was studied whether or not there appears a
waveform representing a hypnagogic symptom. FIGS. 15 to FIGS. 17 which
will be described below each show test results of one of the three
subjects. FIG. 15A shows time-series waveforms of respective gradients of
power values and maximum Lyapunov indexes related to the breath
components obtained from the air cushions 10, and FIG. 15B shows
time-series waveforms of respective gradients of power values and maximum
Lyapunov indexes related to the heartbeat components obtained from the
air cushions 10. Further, FIG. 15C shows time-series waveforms of
frequencies of the heartbeat components and the breath components
obtained from the air cushions 10.

[0112]Incidentally, calculation of the time-series waveform of the
gradient of the power values and the time-series waveform of the gradient
of the maximum Lyapunov indexes uses a method proposed by the present
applicants in Japanese Patent Application Laid-open No. 2004-344612.
Specifically, for the respective time-series signals of the heartbeat
components and the breath components which are detected and separated,
maximum values and minimum values are obtained by smoothing
differentiation by Savitzky and Golay. Then, the maximum values and
minimum values are divided by every five seconds and an average value is
obtained from each of them. The square of the difference between the
respective average values of the obtained maximum values and minimum
values is taken as a power value, and this power value is plotted every
five seconds to make a time-series waveform of the power values. The
gradient of power values is obtained by least square method for a certain
time width Tw (180 seconds), so as to read a global change of the power
values from this time-series waveform. Then, for the next time width Tw,
similar calculation is performed for an overlap time T1 (162 seconds) and
results are plotted. One obtained by sequentially repeating this
calculation (slide calculation) becomes the time-series waveform of the
gradient of the power values. The time-series waveform of the gradient of
the maximum Lyapunov indexes is is obtained similarly by chaos analyzing
the respective time-series signals of the heartbeat components and the
breath components which are detected and separated so as to calculate the
maximum Lyapunov indexes, and thereafter obtaining maximum values and
minimum values by smoothing differentiation similarly to the above and
slide calculation of them.

[0114]Now, as reported in WO2005/092193 by the present applicants, on the
time-series waveform of the power value gradient of the finger tip volume
pulse waves, a waveform with large amplitude appears at low frequency,
and preferably, at this time, a time point when the power value gradient
and the maximum Lyapunov index gradient stably exhibit a phase difference
of substantially 180 degrees in the time-series signal can be judged as a
hypnagogic symptom signal. In the time-series waveforms of FIG. 16A, the
waveform showing this hypnagogic symptom appears in the vicinity of 150
seconds to 500 seconds. Comparing this with the time-series waveforms of
the respective gradients of the breath components and the heartbeat
components obtained from the air cushions 10 of FIGS. 15A, 15B, the power
value gradient of the breath components or the heartbeat components
obtained from the air cushions 10 in an almost same time zone as in FIG.
16A becomes a waveform with large amplitude at low frequency.
Accordingly, it can be seen that a hypnagogic symptom can be captured
using the air cushions 10 of the above embodiment. However, comparing
FIG. 15A with FIG. 15B, in the case of this subject, it is easier to
capture a hypnagogic symptom in the gradient time-series waveform of the
heartbeat components obtained from the air cushions 10 than in that of
the breath components thereof.

[0115]Studying a hypnagogic state and a wakeful state with the
distribution ratios of brain waves shown in FIG. 16B, the moment to enter
sleep is when the distribution ratio of a wave goes under 50% and the
distribution ratio of θ wave starts to increase rapidly.
Accordingly, it is proved that this subject fell asleep at 500 seconds
after the start of experiment, awaked in the middle at 1200 seconds after
the start, and fell asleep again at 1700 seconds after the start.

[0116]Next, the respective degrees of fatigue obtained from the
time-series waveforms of the respective gradients of heartbeat components
and breath components obtained from the air cushions 10 are compared with
the respective degrees of fatigue obtained from the gradient time-series
waveform of the finger tip volume pulse waves of FIG. 16A and shown in
FIGS. 17A, 17B. Consequently, in the case of this subject, the degree of
fatigue calculated from the breath components obtained from the air
cushions 10 matched better in tendency with the degree of fatigue
calculated from the finger tip volume pulse waves than the degree of
fatigue calculated from the heartbeat components. Therefore, it is
desirable that judging of the fatigue of this subject is based on the
degree of fatigue calculated from the breath components. When judging
fatigue, which of breath components and heartbeat components should be
used differs among individuals. Thus, when it is judged using, for
example, the bio-signal analyzer 1 of the present invention incorporated
in the seat 300 for automobile, it is preferable that an arrangement is
made to allow initial setting of which of breath components and heartbeat
components obtained from the air cushions 10 should be selected by
comparing with the degree of fatigue obtained from the finger tip volume
pulse waves in advance. Incidentally, although not shown, almost the same
results as the above subject were obtained from the other two subjects.

TEST EXAMPLE 4

[0117]Next, the effectiveness of bio-signal sampling was verified for when
values of the air pressure variation of the air bags 11, 11 of the air
cushions 10 are addition processed and when they are subtraction
processed. In this test, a subject was tested while seated on the seat
300 of the above test example 1 in a resting state for a predetermined
time. Results are shown in FIGS. 18. FIG. 18A shows original waveforms in
time series of the air bags 11, 11 (one arranged close to a human body is
S1 (detection sensor), and the other is S2 (dummy sensor)), original
waveforms in time series when values of air pressure variations obtained
from the air bags 11, 11 are added (addition waveform), and original
waveforms in time series when the values are subtracted (subtraction
waveform). FIG. 18B shows time-series waveforms of the air bags 11, 11
(the detection sensor and the dummy sensor) with respect to heartbeat
components separated by filtering processing. FIG. 18C shows time-series
waveforms when the time-series waveforms of heartbeat components of the
detection sensor and the dummy sensor of FIG. 18B are addition processed
and when they are subtraction processed. FIG. 18D shows time-series
waveforms of the air bags 11, 11 (the is detection sensor and the dummy
sensor) with respect to breath components separated by filtering
processing. FIG. 18E shows time-series waveforms when the time-series
waveforms of breath components of the detection sensor and the dummy
sensor in FIG. 18C are addition processed and when they are subtraction
processed.

[0118]As is clear from these graphs, it can be seen that the addition
processing allows to detect the air pressure variation accompanying a
bio-signal more prominently than by the values of the individual air bags
11, 11 (the detection sensor and the dummy sensor). Particularly, under
the situation that external vibration during traveling is inputted, the
addition processing allows to prominently pick up values of a part where
a bio-signal is obtained. On the other hand, the subtraction processing
has a possibility to remove the influence of external vibration (noise),
but in this test example, the influence of decreasing the amount of air
pressure variation is larger in the subtraction processing. Thus, it was
found that the addition processing is more effective.

TEST EXAMPLE 5

[0119]Next, a test was conducted regarding a possibility of obtaining
voice signals obtained from the air cushions 10. In this test, the
subject was tested while seated on the seat 300 of the above test example
1 in a resting state for a predetermined time. In the test, after seated
in a resting state for a predetermined time, reading of a book aloud for
60 seconds was repeated. Results are shown in FIGS. 19. FIG. 19A shows a
time-series original waveform obtained from the air cushions 10. From
this graph, a large amplitude variation is seen in the original waveform
when reading aloud. FIG. 19B shows frequency analysis results, in which
there is a peak at 0.3 Hz in a state of not reading aloud where it is
possible to detect breath components, and meanwhile the frequency while
reading aloud is a higher frequency. Consequently, it was found that
voice signals can be sampled with the air cushions 10.

[0120]On the other hand, FIGS. 20 show time-series original waveforms
obtained from the air cushions 10 when three subjects (FIG. 20A is of a
male in his thirties (middle to high voice), FIG. 20B is of a male in his
twenties (low voice), FIG. 20C is of a female in her twenties (thin and
high voice)) read the Japanese syllabary aloud between 30 seconds and 40
seconds, and hum a song between 50 seconds and 60 seconds. From these
graphs, it can be seen that the waveform between 30 seconds and 40
seconds and the waveform between 50 seconds and 60 seconds when a voice
was produced are different prominently before and after these periods.
Further, it can also be seen that how amplitude changes is different
depending on the voice range of each subject. Moreover, from these
points, it can be presumed that the output of air pressure variation in
the air cushions 10 due to propagation of sound is different between when
the muscles are tensed and when they are relaxed. Therefore, from an air
pressure variation accompanying a voice, it can be estimated which of the
sympathetic nervous system and the parasympathetic nervous system is more
active. As a consequence, it is possible to further estimate the state of
LF/HF which is index of sympathetic nervous system activity of heartbeats
and the state of HF which is an index of parasympathetic nervous system
activity.

TEST EXAMPLE 6

[0121]Next, a method to separate breath components from an air pressure
variation obtained from the air cushions 10 and estimate a time-series
waveform of heartbeat components using a time-series waveform of the
breath components will be described.

[0122]First of all, it is assumed that a time-series waveform (g1(t))
and a frequency component (G1(F)) of breath components obtained from
an air pressure variation in the air cushions 10 as well as a frequency
response function (TF) of heartbeat components with respect to the breath
components are known variables, and a time-series waveform (g2(t))
and a frequency component (G2(F)) of heartbeat components are
unknown variables.

[0123]In this case, the frequency component of the heartbeat components
can be obtained from
G2(F)=TF.G1(F)=A1A3-B1B3+(A1A3+B.-
sub.1B3)j

[0124]Then the time-series waveform (g2(t)) of the heartbeat
components is obtained by inverse Fourier transforming (IFFT) the
frequency component (G2(F)) of the heartbeat components, and
consequently, it becomes possible to estimate the time-series waveform of
the heartbeat components from the time-series waveform of the breath
components.

[0129]Then, the amplitude characteristic and the phase characteristic are
obtained from actually measured data, and the frequency response function
(TF) is defined.

[0130]In this example, from each of 20 male and female subjects, the
time-series waveform of breath components was measured from the air
cushions 10, the amplitude characteristic and the phase characteristic
were obtained, and average values thereof were further calculated using
the above equations. Data of average values are shown in FIG. 21A and
FIG. 21B, and these FIG. 21A and FIG. 21B were defined as the frequency
response function (TF).

[0131]Thus, it is possible to estimate the time-series waveform and the
frequency component of heartbeat components from the time-series waveform
of breath components. In addition, as estimation means of heartbeat
components, other than the means using Fourier transform and using the
frequency response functions (TF) of FIG. 21A and FIG. 21B as described
above, it is also possible to use an analysis technique by wavelet
transform.

[0132]The obtained data of heartbeat components can be used for presuming
the aforementioned hypnagogic symptoms. For instance, FIG. 22 shows
graphs showing calculation of the gradient of a frequency relative to a
time axis from time-series changes of the frequency relative to the time
axis. This technique is similar to the technique of calculating the
gradient of power values and the gradient of maximum Lyapunov indexes
described in the test example 3. First, peaks are detected from a
time-series waveform, and peak intervals are defined as T1, T2, T3, and
so on. Next, by the peak intervals, a variation waveform of a frequency
is created. At this time, F and T are represented by a relationship of
F=1/T.

[0133]Next, from the variation waveform of the frequency, gradient
components are calculated using least square method for a time width Tw
(180 seconds). Then, an overlapping time is slid by an overlap time (Rap
(162 seconds)), and gradient components are calculated sequentially by
least square method, the time series of the gradients of the frequency is
created.

[0134]Consequently, variation tendencies of frequencies can be seen. For
example, for a variation tendency of a frequency of heartbeat components,
it is possible to further estimate the state of LF/HF which is index of
sympathetic nervous system activity of heartbeats and the state of HF
which is an index of parasympathetic nervous system activity, by
determining which of LF and HF this value belongs, similarly to the test
example 5.

TEST EXAMPLE 7

[0135]Next, three healthy Japanese male subjects in their twenties to
thirties ("asano" (FIG. 23), "ochiai" (FIG. 24), and "maeda" (FIG. 25))
were seated, vibration with a random waveform was applied in the middle
by a vibrator, and time-series waveforms of heartbeat components and
breath components during vibration were compared. FIG. 23 to FIG. 25 show
results, in each of which the lowest graph shows operation timing of the
vibrator and a vibration waveform, and shows time-series waveforms of
breath components and heartbeat components for the measurement time
corresponding to them. These time-series waveforms are time-series
signals which are filtered through the analog signal processing circuit
and thereafter separated into breath components and heartbeat components,
and are data before calculating gradients of them similar to the test
example 3.

[0136]Looking into FIG. 23 to FIG. 25, it can be seen that all the
subjects presented stable waveforms of heartbeat components and breath
components before the vibration is inputted, but after the vibration is
inputted, fluctuations change in both the heartbeat components and the
breath components according to the magnitude of the vibration. The
magnitude of a fluctuation due to the magnitude of vibration differs
among individuals and is not constant. For example, in the case of the
subject in FIG. 23, the fluctuation in the heartbeat components becomes
small just after the vibration is inputted, and the fluctuation in the
breath components becomes large just after the vibration is input.
Moreover, at 170 seconds and thereafter where the vibration increases,
the fluctuation in breath components of this subject becomes small. In
any case, it can be known that, just by looking at this time-series
waveform detected by the air cushions 10 of the present invention, a
fluctuation different from the preceding fluctuation and the load
increases by the input of vibration. Therefore, before calculating the
gradient time series, a change in human condition can be detected quickly
by analyzing the time-series waveform at this time.

[0137]Regarding the subjects in FIG. 24 and FIG. 25, similarly, there
occurs a change in fluctuations of both heartbeat components and breath
components after the input of vibration. However, regarding breath
components, these two subjects have a fluctuation which increases
gradually at 220 seconds and thereafter where the fluctuations become
large, and it can be seen that they have different responses from the
subject of FIG. 23. From these results, it is possible that individual
differences can be detected by time-series waveforms.

[0138]FIG. 26 to FIG. 28 show time-series waveforms of heartbeat
components and breath components of the respective subjects of FIG. 23 to
FIG. 25 in a static state in the morning, at noon, and at night. From the
time-series waveforms, it can be seen that there is a significant
difference in fluctuations of heartbeat components and breath components
even in the same person due to circadian rhythm. For example, the subject
("asano") in FIG. 26 has a large fluctuation in the morning, and thus it
can be read that this person is not a morning person, and becomes more
stable toward the night. Similarly, it can be read that the subject
("ochiai") in FIG. 27 tends to be stable almost all day, and the subject
("maeda") in FIG. 28 is not a morning person either.

[0139]Noted that in the above embodiment, although the air cushions 10
each having two air bags 11, 11 and being folded in two are used, it may
be arranged that two air bags 11, 11 not connected to each other are
stacked and used. Further, as shown in FIG. 29, it may be arranged that a
buffer material (three-dimensional solid knitted fabric and viscoelastic
urethane) 115 for damping vibration is sandwiched between the two air
bags 11, 11. Further, in the above embodiment, the air cushions 10 are
incorporated in the seat back of the seat 100, but as shown in FIG. 30 it
is not limited to the seat fixed in a vehicle such as automobile or
train. It can be arranged that the air cushions 10 are attached to a seat
back 210 of an auxiliary cushion (cushion for seat) 200, which integrally
includes a seat cushion 220 and the seat back 210 to be used by mounting
on such a seat, and is capable of being bent from the boundary of the
both. Note that the meaning of the "seat" in the present specification
and claims also includes such an auxiliary cushion (cushion for seat)
200.